A confidence interval is a range of values that estimates a population parameter based on a sample. The bootstrapping method creates new data sets from the original sample to estimate parameters, allowing for more accurate results. Different techniques like normal interval, percentile bootstrap, and bias-corrected bootstrap are used to calculate confidence intervals. The advantage of using bootstrapping is that it doesn't rely on assumptions about the distribution shape and is a reliable statistical technique that benefits from modern computers for computation.