# Mercer's Theorem importance

I understood that Mercer's Theorem extends the definition of kernels also for infinite input space.

In Machine Learning realm our training set is always finite and hence the input space is always finite. So why are we interested in infinite input spaces?

Where is the flaw in my reasoning?