I don't have an especially awesome place, but Bayesian Data Analysis by Gelman introduces the basics of Metropolis Hastings and Gibbs Sampling (those are probably the first ones to learn). There are probably quite a few other places to learn about these two algorithms too (including wikipedia). MCMC using Hamiltonian Dynamics by Neal, is the standard reference for Hamiltonian Monte Carlo (what I would suggest learning after those two).