Correlation and Naive Bayes I would like to ask if the Pearson correlation between fields (but not the class field) of a dataset affects somehow the performance of Naive Bayes when applying it to the dataset in order to predict the class field.
As you probably know, naive here implies that the "fields" are independent. So your question boils down to does correlation imply dependence. Yes, it does. See here.

https://stats.stackexchange.com/questions/113417/does-non-zero-correlation-imply-dependence

So, if your features show correlation then this will have an adverse effect on the naive assumption. Despite this fact, Naive Bayes has been shown to be robust against this assumption. If your model still suffers from this, however, you could consider transforming the space to be independent with methods such as PCA.