NLP methods specific to a language?
This question is quite open, but nonetheless, here are some:

lemmatization/stemming only makes sense in languages where there is a lemma/stem in the word. Some languages like Chinese have no morphological variations (apart from some arguable cases like the explicit plural 们), and therefore lemmatization and stemming are not applied in Chinese.

Word-based vocabularies are used to represent text in many NLP systems. However, in agglutinative and polysynthetic languages, using word-level vocabularies is crazy, because you can put together a lot of affixes and form a new word, therefore, a prior segmentation of the words is needed.

In some languages like Chinese and Japanese, there are no spaces between words. Therefore, in order to apply almost any NLP, you need a preprocessing step to segment text into words.