How to Put Machine Learning in your Machine Learning

There are so many Machine Learning algorithms and so many parameters for each one. Why can't we just use a meta-algorithm (maybe even one that uses Machine Learning) to select the best algorithm and parameters for our dataset? Many Machine Learning problems are formalized as an optimization wherein you're given some data, there are some free parameters, and you have some sort of function to measure the performance of those parameters on that data. Your goal is to choose the parameters to minimize (or maximize) the given function. But this sounds exactly like what we do when we select a Machine Learning algorithm!