The Bootstrap Method is a statistical technique used to estimate the distribution of a sample statistic by resampling with replacement from the original data. This method allows researchers to create multiple simulated samples, which helps in assessing the variability and confidence intervals of estimates without relying on traditional assumptions about the data's distribution. This approach is particularly useful in situations where the sample size is small or when the underlying distribution is unknown. By generating a large number of resampled datasets, the Bootstrap Method provides a robust way to make inferences about population parameters, enhancing the reliability of statistical conclusions.