In NLP, languages are often referred as low resource or high resource.
What do these terms mean?
High resource languages are languages for which many data resources exist, making possible the development of machine-learning based systems for these languages. English is by far the most well resourced language. West-Europe languages are quite well covered, as well as Japanese and Chinese. Naturally low-resource languages are the opposite, that is languages with none or very few resources available. This is the case for some extinct or near-extinct languages and many local dialects. There are actually many languages which are mostly oral, for which very few written resources exist (let alone resources in electronic format); for some there are written documents but not even something as basic as a dictionary.
There are many different types of resources which are needed in order to train good language-based systems:
Many types of language resources are costly to produce, this is why the economic inequalities between countries/languages are reflected in the amount (or absence) of language resources. The Universal Dependencies project is an interesting effort to fill this gap.