Bootstrap methods are a powerful statistical tool used to estimate the sampling distribution of an estimator by resampling with replacement from the data. These methods allow for the assessment of the variability of a statistic without relying on strong parametric assumptions, making them particularly useful for complex data structures or small sample sizes.