Latin Hypercube Sampling (LHS) is a statistical method used for generating a distribution of plausible collections of parameter values from a multidimensional distribution. It ensures that each parameter is sampled across its entire range, thus providing a more comprehensive exploration of the input space compared to simple random sampling.