Variance Reduction Techniques are strategies used in statistical simulations and Monte Carlo methods to decrease the variance of an estimator, thereby improving the precision of the results without increasing the number of simulations. These techniques are crucial for enhancing computational efficiency and accuracy in estimating expected values and probabilities in complex models.