A minimal polynomial is the monic polynomial of the smallest degree that a matrix satisfies, while the characteristic polynomial is derived from the eigenvalues of the matrix. For example, the matrix A has a characteristic polynomial of (λ - 2)², but its minimal polynomial is λ - 2, as it satisfies A - 2I = 0. In contrast, matrix B has the same characteristic polynomial but does not satisfy A - 2I = 0, making its minimal polynomial identical to its characteristic polynomial. The minimal polynomial must include all eigenvalues as factors, and when a matrix has multiple eigenvalues with independent eigenvectors, the minimal polynomial can be of lower degree than the characteristic polynomial. Understanding these distinctions is crucial in abstract algebra and matrix theory.