There are at least two senses of what we might mean here. Both of these have separate and distinct standards of proof, and for both, it is impossible to furnish such a proof. In both of them, the question comes down to, fundamentally, "what is the microscopic structure of the points on a line?" That is, "how can we describe all the points thereupon individually and their relationships to each other in an explicit, concrete manner based on indisputable constructs?" There are, in fact, mathematically, many, many different ways you can array such points and many different levels of detail at which you can talk of such arrangements which, makes this question all the more pertinent and definitely far from as obvious as you might at first think having been conditioned by teaching, drilling, and reprimand/"takemywordism".
- One of these is a purely mathematico-philosophic sense: does the real number line faithfully represent what we intuitively think distances are? This is actually something known as the "Cantor-Dedekind Thesis", and it asserts this in the affirmative or, more precisely, that the line intended and honoerd in the tradition of ancient Greek geometry and its modern elaborations in the post-classical eras of European and Islamic history, has its microstructure best captured by the modern real line construct of Dedekind.
- The second one is a question of physics and empirical science, specifically application to the Universe we live in: does the real number line faithfully capture the microstructure of the distances along a real line (where "real" means reality and not "real numbers") between two points in the real world space in which our actual lives take place?
We cannot provide a proof for either one. In the first case, different people may have different intuitions and, moreover, from a purely formally mathematical view, this thesis is like others such as the "Church-Turing thesis" regarding computation: it's basically an assertion of a standard position on the meaning of a term - here "distance" or "microstructure of the line", there, "computation" - that is inherently subject to contestability. Meaning is not something that can be proven/refuted: as the age-old question of prescriptivism in language illustrates.
For the second one, we can, at best, disprove this by showing that there existed, say, an absolute minimum distance scale. (The Planck length, by the way, is merely a proposal for such a scale - it is not by any means proven that this is and, in fact, there may be some evidence against it being so.) We cannot actually prove that the structure of physical space really is that of the real number line, or anything else that involves questions of what it looks like with infinite resolution, because all our empirical measurements can only ever have finite resolution if by nothing other than the simple fact that we cannot actually store the infinite amount of information that an infinitely precise measurement would represent. This means that there is no empirical way to distinguish physical space from being isomorphic to $\mathbb{R}$, or to a pixelated space with grain size $10^{-\mbox{Graham's number}}\ \mbox{US survey feet}$. Or, from the hyperreal and surreal numbers, or from more restricted but still rather complex systems like the computable numbers, which posit differences in detail at inaccessible infinitely fine scales. All we can surmise is that the space is at least as detailed and fine as the best measurements we have made so far.
In the end, $\mathbb{R}$ is a scientific model, just like all other parts of our physical theories are models, and that is used to represent physical space in all theories that are actually empirically validated. At no point should a model be assumed to be reality, but rather is a story we tell about and language we use to talk about, reality, and its empirical validation that it is a way of talking about reality that is faithful thereto in that it won't lead us to believe things happen that don't or that don't happen that do, to the extent thereof. There are likely many, many other stories we could tell thereabout that are just as good but for which historical contingency has effectively blinded us to.
And the reason we use $\mathbb{R}$ for building models is chiefly one of convenience: $\mathbb{R}$ is very nice to work with mathematically. Conceptually, it enjoys a simple structure: effectively, it can be considered as the natural result of wanting an integrated, streamlined number system in which you can talk about measurements at arbitrary levels of precision, up to a "clean" infinite precision which is useful for theoretical purposes. (Indeed, it is not too hard at all to hop from that to a formal definition or at least axiomatization.) Moreover, as such it ends up being very clean when it comes to formulating things like calculus, an indispensible tool of modern practice and physical and scientific model-building.
None of the other proposed alternatives to it - and there are many - have, so far, shown themselves to be quite as nice for model-building. If reality isn't so nice, fine, but even if we could somehow prove that, $\mathbb{R}$ would still continue to be very useful in working with approximate models for situations where we can ignore its true structure - e.g. pretty much all vocational and technological applications today. Even today, it is used in cases where we do know that the underlying phenomena aren't really like $\mathbb{R}$, e.g. many population growth models describe population as a real number, so one can avail oneself of tools like calculus in building them, even though of course we know that real populations of real organisms can only ever be whole numbers. $\mathbb{R}$ is literally that damn good.