I used following command to filter out 3 groups (NC, BF, CF) out of 5 groups while remaining two groups are "AF" and "DF".

design_NCaF <- filter(design, Groups1!="NC",Groups1!="BF",Groups1!="CF")

However, at following command

NCaF <- DESeqDataSetFromMatrix(data_max_woNCaF, colData=design_NCaF, design = ~Groups1 + Patient)

It gives me following error message 

factor levels were dropped which had no samples
Error in checkFullRank(modelMatrix) : 
  the model matrix is not full rank, so the model cannot be fit as specified.
  One or more variables or interaction terms in the design formula are linear
  combinations of the others and must be removed.

Is it because of remaining two groups have different sample size (AF=6 and DF=3) ?

You need to droplevels() from the factor after filtering, e.g. if you filter out samples from 'group':

dds$group <- droplevels(dds$group)