The Laplacian matrix is a representation of a graph that captures the connectivity and structure of the graph, and is widely used in fields such as spectral graph theory and network analysis. It is defined as the difference between the degree matrix and the adjacency matrix, and its eigenvalues and eigenvectors provide valuable insights into properties like connectivity, spanning trees, and clustering within the graph.