The Gauss-Markov Theorem states that in a linear regression model where the errors have expectation zero, are homoscedastic, and uncorrelated, the ordinary least squares (OLS) estimator is the best linear unbiased estimator (BLUE) of the coefficients. This means that among all linear and unbiased estimators, OLS has the smallest variance, making it the most efficient choice under these conditions.