A matrix is singular if its determinant is zero, indicating that it cannot be inverted. This occurs because a zero determinant means the linear transformation associated with the matrix flattens the n-dimensional volume, making it non-one-to-one. Consequently, at least one eigenvalue must be zero, leading to the existence of a non-zero vector that results in a zero product when multiplied by the matrix. The determinant can also be understood as a measure of volume spanned by the matrix's column vectors. Overall, the determinant's properties are crucial for understanding the invertibility of matrices and their transformations.