A covariance matrix is a square matrix that provides a measure of how much two random variables change together, with diagonal elements representing variances and off-diagonal elements representing covariances. It is a fundamental tool in multivariate statistics, used to understand the relationships between variables and to perform dimensionality reduction techniques like Principal Component Analysis (PCA).