The Box-Cox Transformation is a statistical technique used to stabilize variance and make data more closely conform to a normal distribution, enhancing the validity of parametric statistical tests. It involves identifying an optimal lambda parameter that transforms the data, with common transformations including logarithmic and square root transformations as special cases.