Bootstrap resampling estimates the sampling distribution of a statistic by drawing repeatedly from your observed sample with replacement. You recompute the statistic on each resample to build a picture of its variability when the true distribution is unknown. It is common for confidence intervals and for checking how stable a model result is. Do not confuse statistical bootstrapping with the yield-curve bootstrap that builds spot rates from coupon bonds.