Natural Language Processing (NLP) is the field of AI that lets machines read, interpret, and generate human language. It is the technology behind search engines making sense of messy queries, chatbots holding a conversation, and tools that pull meaning — entities, sentiment, intent — out of plain text.
When you type a half-formed query, NLP closes the gap between your words and your meaning. Google's BERT update was a landmark. Take the search "2019 brazil traveler to usa need a visa": an older system might have skipped the small word "to", but direction of travel changes the answer entirely. BERT reads the sentence in context and understands the traveller is going from Brazil to the USA, so the result reflects a Brazilian's real need rather than the reverse.
Because engines now parse language instead of matching strings, writing naturally beats gaming exact phrases. NLP extracts entities, gauges topical depth, and reads user intent, so content that answers the real question in clear prose tends to win. It is also why synonyms and related concepts help — the machine reads for meaning, not for a repeated keyword.
The two are easy to confuse. NLP is the broad field of understanding and working with language; natural language generation is the narrower task of producing text. Reading a customer review and tagging its sentiment is NLP; writing a summary of a hundred such reviews is NLG.