Node classification is a task in graph-based machine learning where the goal is to assign labels to nodes within a graph. Each node represents an entity, and the connections between them, or edges, indicate relationships. This process helps in understanding the characteristics of nodes based on their features and the structure of the graph. In node classification, algorithms analyze the features of nodes and their neighbors to predict the labels. Common applications include social network analysis, where users are classified into groups, and biological networks, where proteins or genes are categorized. Techniques like graph neural networks are often employed to enhance classification accuracy.