Have a look at the fitcnb command from the Statistics and Machine learning toolbox. Here is a link to the documentation:

https://se.mathworks.com/help/stats/fitcnb.html

data=[x1,y1,z1]; %a matrix of n*m

%labl a vector of n*1

ObjBayes = NaiveBayes.fit(data, labl);

lablPredict = ObjBayes.predict(data2); % data2 a matrix of n2*m

%lablPredict a vector of n2*1

Mdl = fitcnb(X,Y) returns a multiclass naive Bayes model (Mdl), trained by predictors X and class labels Y

@ Faraz Akram sir multi class naive Bayes model is also train and predict as multi class SVM classifier??

this link will help you

https://stackoverflow.com/questions/58674455/how-to-use-fitcnb-naive-bayes-in-matlab-with-discrete-attributes

if you have 10 classes first of all you should make a model and then use the model for naive Bayes classifying

be aware of that train and test data must be float

Mdl = fitcnb(Train,Class,'CategoricalPredictors',[1 2 3 4 5 6 7 8 9 10]);

Class_test_result = predict(Mdl,Test)