What Are Embeddings in Natural Language Processing?

In NLP, embeddings transform words, sentences, and documents into dense vectors that encode linguistic meaning geometrically. They allow models to understand that 'happy' and 'joyful' are synonymous, that 'Paris' relates to 'France' the way 'Tokyo' relates to 'Japan', and that sentence meaning persists across paraphrase.