Graph Neural Networks (GNNs) are a type of neural network that operates on graph structures, where nodes represent entities and edges represent relationships. GNNs excel in tasks like social network analysis, molecule prediction, and recommendation systems, as they effectively capture the dependencies between nodes in graphs.