Bootstrapping is a method to understand the uncertainty of a measurement on a sample. Bootstrapping is based on resampling and repeating the measurement to have an idea of its distribution of possible values over other samples of the same size.
Imagine that we want to measure the mean height of the people in a country. To have an idea of that value, we can draw a representative sample of people in the country such that it has similar fraction of people of the gender, age, ethnicity, etc as the country. We can measure the mean over that sample, but how certain are we of that measure? What other values for the mean could we expect if we produced another sample?