Conceptual Understanding of ANOVA Tests

In an ANOVA test, we are testing different sample variances and comparing them using them to form an F-ratio. In my textbook, the conclusion is made that:
1. Null hypothesis is true: F ratio is aobut 1 because MS(between) and MS (within) are about the same.
2. Null hypothesis is false: F ratio is greater than 1 because MSB increases while MSW stays about the same.

My question is, how does the null hypothesis relate to the ANOVA test. Could you please explain what are we trying to reject here, what is the conceptual understanding behind null hypotheses and ANOVA tests that will allow me to understand the 2 conclusions above?

Thanks