Node embeddings are a technique used to represent nodes in a graph as vectors in a continuous vector space, capturing both the graph's structural information and node-specific attributes. These embeddings facilitate various machine learning tasks such as node classification, link prediction, and clustering by enabling the application of traditional machine learning algorithms on graph data.