Shrinkage estimation is a method used to estimate the average of a group of numbers. It involves shrinking the observed values towards zero to get a more accurate estimate. This technique was developed by Stein and later improved by James and Stein. While shrinkage estimators work well for normal distributions, they are not as effective for finite sample spaces like the binomial distribution. The approach also has connections to Bayesian and empirical Bayes methods.