First, made some sample data and calculated frequency table with function table().
 df<-data.frame(Sex=sample(c(2,3),10,replace=TRUE),Country=sample(c(4,5),10,replace=TRUE))
 table4<-table(df)
 table4
   Country
Sex 4 5
  2 4 1
  3 2 3
With function str() you can see structure of table4. Sex levels 2 and 3 are stored as dimension names. So you can replace them using function attr() and selecting $Sex. 
 str(table4)
 'table' int [1:2, 1:2] 4 2 1 3
 - attr(*, "dimnames")=List of 2
  ..$ Sex    : chr [1:2] "2" "3"
  ..$ Country: chr [1:2] "4" "5"
 attr(table4,"dimnames")$Sex<-c("Female","Male")
Now plot changed table4 object.
plot(table4,main="Frequency table",xlab= "Gender", ylab="Country" )
