The Hessian matrix is a square matrix of second-order partial derivatives of a scalar-valued function, providing insight into the local curvature of the function. It is crucial in optimization, as it helps determine whether a critical point is a local minimum, maximum, or saddle point by analyzing the eigenvalues of the matrix.