Comparing four groups by running a t-test on every pair means six tests. Why does that inflate the false positive rate, and what does ANOVA do instead?

B. Because each test carries its own 5% risk across six comparisons.

Each test is fine on its own and the problem is arithmetic across tests: 0.95 to the sixth power is about 0.74, so the chance of at least one spurious result is roughly 26%. ANOVA asks one omnibus question at one alpha. It is the same multiple-comparisons problem that appears as undisclosed analytic flexibility, wearing a second costume.