Self-attention is a technique used in models to determine which parts of a sequence (like a sentence) are important when generating predictions. In the context of natural language processing, it helps the model focus on relevant words in a sentence by computing a score for each word relative to others. This is essential for understanding context and meaning, improving tasks like language translation and text generation.