You have shown only a small portion of the report for your fit. The Whole Model Test is just that - is the model you proposed, as a whole, significant compared to the base model. The test is based the likelihood of the parameters given the data. The likelihood is computed for both the base model and the whole model, and then compared by ratio. This statistic has a chi square distribution under the null hypothesis.
The Goodness of Fit report provides two new insights. The Pearson statistic is another Chi square statistic that tests for 'over dispersion,' which means that the variance of the response is not fully accounted for. Your model exhibits high over dispersion. The Deviance chi square is a test for lack of fit. It compares the likelihood of the full model to that of a 'saturated model.' Your model exhibits large lack of fit.
It seems odd that the Chi square for over-dispersion and for deviance is the same. Can you provide more details about the data and the model you are using?
What led you to use a GLM if you are not familiar with them?
