Bootstrap Resampling is a statistical technique used to estimate the distribution of a sample statistic by repeatedly sampling with replacement from the original dataset. This method allows researchers to create multiple simulated samples, which helps in assessing the variability and reliability of the statistic, such as the mean or median. By generating many resampled datasets, Bootstrap Resampling provides a way to calculate confidence intervals and perform hypothesis testing without relying on traditional assumptions about the data's distribution. This flexibility makes it a valuable tool in various fields, including data science and biostatistics.