It might be useful (I'm not sure) to think of the F statistic in terms of R^2 where:

F = [R^2/p]/[(1-R^2)/(N-p-1)].

Do you understand the interpretation of what the value of R^2 means?

The null hypothesis states (in English) that you are not going to get any help at all in predicting Y (D.V.) from any of the X's (I.V.'s). That is, you may as well just you the mean of Y (Y_bar) as the best predictor of Y because Y_bar is the OLS estimate of Y.

The alternative hypothesis states (in English) that you will get some help from at least one (perhaps more) of the X's in predicting Y.

The (F) ratio does not automatically support the alternative hypothesis i.e. or, conversely, automatically reject the null hypothesis.