The variance-covariance matrix is a square matrix that encapsulates the variances of individual variables along its diagonal and covariances between pairs of variables in its off-diagonal elements, providing a comprehensive snapshot of how variables vary with respect to each other. It is a fundamental tool in multivariate statistics, enabling the assessment of the linear relationship between variables and playing a crucial role in portfolio optimization, risk management, and principal component analysis.