Contextual embeddings are advanced word representations that capture the meaning of words based on their context within a sentence, enabling more nuanced understanding and processing of language. Unlike static embeddings, contextual embeddings dynamically adjust to the surrounding text, making them crucial for tasks like machine translation, sentiment analysis, and question answering.